mirror of
https://github.com/superseriousbusiness/gotosocial.git
synced 2024-12-05 18:12:46 +00:00
170 lines
3.7 KiB
Go
170 lines
3.7 KiB
Go
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package imaging
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import (
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"image"
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"math"
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)
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func gaussianBlurKernel(x, sigma float64) float64 {
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return math.Exp(-(x*x)/(2*sigma*sigma)) / (sigma * math.Sqrt(2*math.Pi))
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}
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// Blur produces a blurred version of the image using a Gaussian function.
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// Sigma parameter must be positive and indicates how much the image will be blurred.
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//
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// Example:
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//
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// dstImage := imaging.Blur(srcImage, 3.5)
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//
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func Blur(img image.Image, sigma float64) *image.NRGBA {
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if sigma <= 0 {
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return Clone(img)
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}
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radius := int(math.Ceil(sigma * 3.0))
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kernel := make([]float64, radius+1)
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for i := 0; i <= radius; i++ {
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kernel[i] = gaussianBlurKernel(float64(i), sigma)
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}
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return blurVertical(blurHorizontal(img, kernel), kernel)
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}
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func blurHorizontal(img image.Image, kernel []float64) *image.NRGBA {
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src := newScanner(img)
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dst := image.NewNRGBA(image.Rect(0, 0, src.w, src.h))
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radius := len(kernel) - 1
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parallel(0, src.h, func(ys <-chan int) {
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scanLine := make([]uint8, src.w*4)
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scanLineF := make([]float64, len(scanLine))
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for y := range ys {
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src.scan(0, y, src.w, y+1, scanLine)
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for i, v := range scanLine {
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scanLineF[i] = float64(v)
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}
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for x := 0; x < src.w; x++ {
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min := x - radius
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if min < 0 {
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min = 0
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}
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max := x + radius
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if max > src.w-1 {
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max = src.w - 1
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}
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var r, g, b, a, wsum float64
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for ix := min; ix <= max; ix++ {
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i := ix * 4
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weight := kernel[absint(x-ix)]
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wsum += weight
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s := scanLineF[i : i+4 : i+4]
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wa := s[3] * weight
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r += s[0] * wa
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g += s[1] * wa
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b += s[2] * wa
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a += wa
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}
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if a != 0 {
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aInv := 1 / a
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j := y*dst.Stride + x*4
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d := dst.Pix[j : j+4 : j+4]
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d[0] = clamp(r * aInv)
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d[1] = clamp(g * aInv)
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d[2] = clamp(b * aInv)
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d[3] = clamp(a / wsum)
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}
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}
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}
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})
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return dst
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}
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func blurVertical(img image.Image, kernel []float64) *image.NRGBA {
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src := newScanner(img)
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dst := image.NewNRGBA(image.Rect(0, 0, src.w, src.h))
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radius := len(kernel) - 1
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parallel(0, src.w, func(xs <-chan int) {
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scanLine := make([]uint8, src.h*4)
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scanLineF := make([]float64, len(scanLine))
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for x := range xs {
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src.scan(x, 0, x+1, src.h, scanLine)
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for i, v := range scanLine {
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scanLineF[i] = float64(v)
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}
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for y := 0; y < src.h; y++ {
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min := y - radius
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if min < 0 {
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min = 0
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}
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max := y + radius
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if max > src.h-1 {
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max = src.h - 1
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}
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var r, g, b, a, wsum float64
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for iy := min; iy <= max; iy++ {
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i := iy * 4
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weight := kernel[absint(y-iy)]
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wsum += weight
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s := scanLineF[i : i+4 : i+4]
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wa := s[3] * weight
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r += s[0] * wa
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g += s[1] * wa
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b += s[2] * wa
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a += wa
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}
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if a != 0 {
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aInv := 1 / a
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j := y*dst.Stride + x*4
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d := dst.Pix[j : j+4 : j+4]
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d[0] = clamp(r * aInv)
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d[1] = clamp(g * aInv)
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d[2] = clamp(b * aInv)
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d[3] = clamp(a / wsum)
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}
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}
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}
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})
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return dst
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}
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// Sharpen produces a sharpened version of the image.
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// Sigma parameter must be positive and indicates how much the image will be sharpened.
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//
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// Example:
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//
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// dstImage := imaging.Sharpen(srcImage, 3.5)
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//
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func Sharpen(img image.Image, sigma float64) *image.NRGBA {
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if sigma <= 0 {
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return Clone(img)
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}
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src := newScanner(img)
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dst := image.NewNRGBA(image.Rect(0, 0, src.w, src.h))
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blurred := Blur(img, sigma)
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parallel(0, src.h, func(ys <-chan int) {
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scanLine := make([]uint8, src.w*4)
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for y := range ys {
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src.scan(0, y, src.w, y+1, scanLine)
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j := y * dst.Stride
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for i := 0; i < src.w*4; i++ {
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val := int(scanLine[i])<<1 - int(blurred.Pix[j])
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if val < 0 {
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val = 0
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} else if val > 0xff {
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val = 0xff
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}
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dst.Pix[j] = uint8(val)
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j++
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}
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}
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})
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return dst
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}
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